
using the coordinate descent algorithm [1]}. The method consists in partially minimizing (\(\ref {eq:glmnet}\) ) with respect to \(\beta _j\)  given \(\check{\beta }_l\)  for \(l \ne j\) , \(l,j=1,\ldots ,p\) , that is
\( {\displaystyle \min _{\beta _j} \Omega (\check{\beta }_1, \ldots , \check{\beta }_{j-1}, \beta _j, \check{\beta }_{j+1}, \ldots , \check{\beta }_{p})}.\) 
